PROSITE is copyright.
There are no restrictions on its use by non-profit
institutions as long as its content is in no way modified. Usage by and
for commercial entities requires a license agreement. For information about
the licensing scheme see the
prosite license
or send an email to Prosite License.
The above copyright notice also applies to this user manual as well
as to any other PROSITE document.

I.C. Introduction

PROSITE is a method of determining what is the function of uncharacterized
proteins translated from genomic or cDNA sequences. It consists of a database
of biologically significant sites and patterns formulated in such a way
that with appropriate computational tools it can rapidly and reliably identify
which known family of protein (if any) the new sequence belongs to.

In some cases the sequence of an unknown protein is too distantly related
to any protein of known structure to detect its resemblance by overall
sequence alignment, but it can be identified by the occurrence in its sequence
of a particular cluster of residue types which is variously known as a
pattern, motif, signature, or fingerprint. These motifs arise because of
particular requirements on the structure of specific region(s) of a protein
which may be important, for example, for their binding properties or for
their enzymatic activity. These requirements impose very tight constraints
on the evolution of those limited (in size) but important portion(s) of
a protein sequence. To paraphrase Orwell, in Animal Farm, we can say that
"some regions of a protein sequence are more equal than others" !

The use of protein sequence patterns (or motifs) to determine the function(s)
of proteins is becoming very rapidly one of the essential tools of sequence
analysis. This reality has been recognized by many authors, as it can be
illustrated from the following citations from two of the most well known
experts of protein sequence analysis, R.F. Doolittle and A.M. Lesk:

"There are many short sequences that are often (but not always)
diagnostics of certain binding properties or active sites. These can be
set into a small subcollection and searched against your sequence (1)".

"In some cases, the structure and function of an unknown protein
which is too distantly related to any protein of known structure to detect
its affinity by overall sequence alignment may be identified by its possession
of a particular cluster of residues types classified as a motifs. The motifs,
or templates, or fingerprints, arise because of particular requirements
of binding sites that impose very tight constraint on the evolution of
portions of a protein sequence (2)."

Based on these observations we decided, in 1988, to actively pursue
the development of a database of patterns which would be used to search
against sequences of unknown function. This database, called PROSITE, contains
a few patterns which have been published in the literature, but the majority
have been developed, in the last ten years by the author. Originally this
dictionary was conceived as part of the author's doctoral dissertation
as well as an integral part of the PROSITE program in the PC/Gene sequence
analysis software package. But, as many people have expressed their interest
in this project, we have decided to make this work available on computer
media.

There are a number of protein families as well as functional or structural
domains that cannot be detected using patterns due to their extreme sequence
divergence; the use of techniques based on weight matrices (also known
as profiles) allows the detection of such proteins or domains. In 1994
we started a collaborative project with Philipp Bucher to introduce profiles
in PROSITE. Currently, most of the new PROSITE entries are centered around
profiles and are developed by the PROSITE collaborators at the SIB Swiss Institute of
Bioinformatics in Geneva and Lausanne.

PROSITE consists of documentation entries describing protein domains, families and functional
sites, as well as associated patterns and profiles to identify them
[More...].
PROSITE is complemented by ProRule, a collection of rules based on profiles and patterns,
which increases the discriminatory power of profiles and patterns by providing additional
information about functionally and/or structurally critical amino acids
[More...].

The following table shows the growth of the database since its creation in 1989
up to release 20.0 in 2010:

ProRule: a new database containing functional and structural information on PROSITE profiles.

Bioinformatics. 21:4060-4066(2005).

If you want to refer to the stand-alone tool to scan PROSITE please cite:

Gattiker A., Gasteiger E. and Bairoch A.;

ScanProsite: a reference implementation of a PROSITE scanning tool

Applied Bioinformatics 1:107-108(2002)

I.G. Feedback

We welcome any feedback. If you find errors, omissions, or if you want
to suggest new sites, patterns or profiles to be added to this database, please
let us know. You can contact us (by electronic mail preferably) at
prosite.expasy.org/contact.

II. PROSITE methodology

II.A. Patterns development

In this section we will explain how we selected or developed the signature
patterns described in this compilation. Our first and most important criterion
is that a good signature pattern must be as short as possible, should detect
all or most of the sequences it is designed to describe and should not
give too many false positive results. In other words it must exhibit both
high sensitivity and high specificity.

II.A.1. Patterns from the literature

A number of the patterns described in this dictionary have been published.
We have tested those patterns on the Swiss-Prot part of UniProtKB to see if the
signature pattern was still specific to the group of family of proteins
since the paper was published. If this was the case we used the published
pattern as such, otherwise we updated the pattern using methods similar
to those used to develop a new pattern and which are described in the following
sub-section.

II.A.2. Steps in the development of a new pattern

We generally start by studying review(s) on a group or family of proteins.
We build an alignment table of the proteins discussed in that review. If
necessary we add to this table new published sequences relevant to the
subject under consideration. Using such alignment tables we pay particular
attention to the residues and regions thought or proved to be important
to the biological function of that group of proteins. These biologically
significant regions or residues are generally:

We then try to find a short (not more than four or five residues long)
conserved sequence which is part of a region known to be important or which
include biologically significant residue(s). We call the pattern(s) created
at this stage the 'core' pattern(s). The most recent version of the Swiss-Prot
part of UniProtKB is then scanned with these core pattern(s). If
a core pattern will detect all the proteins under consideration and none
(or very few) of the other proteins, we can stop at this stage and use
the core pattern as a bona fide signature. In most cases we are not so
lucky and we pick up a lot of extra sequences which clearly do not belong
to the group of proteins under consideration. A further series of scans,
involving a gradual increase in the size of the pattern, is then necessary.
In some cases we never manage to find a good pattern and we have to retry
with a core pattern from a different part of the sequence. It must also
be noted that we take particular attention to try to avoid 'false' patterns.
We will use an example to describe what we call a 'false' pattern:

Let us assume that we have a partial alignment of three sequences around
an active site residue (in this example an histidine whose position is
marked with an asterisk) as shown below:

*
ALRDFATHDDF
SMTAEATHDSI
ECDQAATHEAS

Here we would start scanning with a core pattern with the sequence A-T-H-[D
or E]. This pattern is small and would probably pick up too many false
positive results. According to the procedure outlined above, we would then
have to extend the core pattern. But in this case, any extension would
be artificial and group together residues which have different properties
and which are represented only once in a given position of the alignment.
For example, we could scan with the pattern [R, T or D]-[D, A or Q]-[F,
E or A]-A-T-H-[D or E]. This pattern would probably only pick up the sequences
which are in the alignment, but it would be biologically meaningless; there
is no consensus in the first three positions of the pattern and the pattern
does not even group residues with identical physicochemical properties.
Consequently, this pattern would probably fail to detect a new sequence
containing the same active site but having a different N-terminal sequence.

II.B. Profiles development

A profile or weight matrix (the two terms are used synonymously here)
is a table of position-specific amino acid weights and gap costs. These
numbers (also referred to as scores) are used to calculate a similarity
score for any alignment between a profile and a sequence, or parts of a
profile and a sequence. An alignment with a similarity score higher than
or equal to a given cut-off value constitutes a motif occurrence. As with
patterns, there may be several matches to a profile in one sequence, but
multiple occurrences in the same sequences must be disjoint (non-overlapping)
according to a specific definition included in the profile.

The profile structure used in PROSITE is similar to but slightly more
general than the one introduced by Gribskov and co-workers (3). Additional
parameters allow representation of other motif descriptors, including the
currently popular hidden Markov models. A technical description of the
profile structure and of the corresponding motif search method is given
in the file
profile.txt included in each PROSITE release.

Profiles can be constructed by a large variety of different techniques.
The classical method developed by Gribskov and co-workers (4) requires a
multiple sequence alignment as input and uses a symbol comparison table
to convert residue frequency distributions into weights. The profiles included
in the current PROSITE release were generated by this procedure applying
recent modifications described by Luethy and co-workers (5). In the future,
we intend to apply additional profile construction tools including structure-based
approaches and methods involving machine learning techniques. We also consider
the possibility of distributing published profiles developed by others
in PROSITE format along with locally produced documentation entries.

Unlike patterns, profiles are usually not confined to small regions
with high sequence similarity. Rather they attempt to characterize a protein
family or domain over its entire length. This can lead to specific problems
not arising with PROSITE patterns. With a profile covering conserved as
well as divergent sequence regions, there is a chance to obtain a significant
similarity score even with a partially incorrect alignment. This possibility
is taken into account by our quality evaluation procedures. In order to
be acceptable, a profile must not only assign high similarity scores to
true motif occurrences and low scores to false matches. In addition, it
should correctly align those residues having analogous functions or structural
properties according to experimental data.

Profiles are supposed to be more sensitive and more robust than patterns
because they provide discriminatory weights not only for the residues already
found at a given position of a motif but also for those not yet found.
The weights for those not yet found are extrapolated from the observed
amino acid compositions using empiric knowledge about amino acid substitutability.
The effect of such a procedure is exemplified below.

Shown are a short alignment without gaps and the corresponding weighting
table derived with our standard method.

Note that at certain positions, a residue not occurring in the
alignment receives a higher score than one occurring in the alignment,
as a result of other residues at that position. Thus A occurring in the
third column has a lower score (-1) than M (+10) not occurring there but
physicochemically similar to L, I, V, F found in the other sequences. Similar
extrapolation procedures are used to derive position-specific insertion
and deletion scores which further enhance the selectivity of the profile.

II.C. Repeats identification

Generally repeats possess high amino acid substitution rates and their identification is highly problematic.
Even if the presence of a certain repeat family is known, the exact locations and number of repetitive units
often cannot be determined using current profile search. We have implemented a context dependent threshold that allows
the detection of strongly divergent repeats when well characterized ones have already been identified.

Our approach aims to set a lower acceptance threshold for sub-optimal alignments of profiles to proteins containing repeats. This is accomplished by scanning the profile against a randomized database of sequences where the occurrence of at least one copy of the repeat has been assessed with high confidence. The computed lower acceptance threshold is then used both for the detection of additional copies of the same repeat within the protein, and for the identification of new distantly related members of the protein family.

Two complementary approaches were designed to increase the sensitivity of profiles for the detection of repeats. One approach, Repeats Detection Method 1 (RDM1) consists in defining (computing) a low acceptance threshold placed at level -1 in the profile. For simplicity we will call level 0 cutoff protein-threshold and level -1 cutoff minimal-threshold. When the profile is compared with a given sequence a list of matches with scores greater than the minimal-threshold is collected. The matches are considered as significant, only if at least a hit with a score greater than the protein-threshold has been detected in the target protein. In a target sequence, where the occurrence of a particular domain has been reported, the minimal-threshold represents the score above which the probability of detecting additional copies of the same domain by chance is close to zero.

However, the detection of repeats in proteins where no single domain scores above the protein-threshold remains critical. This is typically the case for more distantly related members of a protein family. To obviate this problem a second approach was devised, Repeats Detection Method 2 (RDM2). The sum of the scores of alignments with scores greater than the minimal-threshold is computed. If the sum of the individual domain scores is larger than a threshold (the sum-of-scores-threshold), these domains are considered to be true homologues. Based on the inspection of the list of positive hits found upon databases searches, we found that a good estimate for the sum-of-scores-threshold is the value of the sum of the protein-threshold with the minimal-threshold. This value was chosen since it represents in theory the minimal match score that would be detected when aligning a profile to a member of a given protein family containing only two copies of a repeat.

RDM1 and RDM2 were implemented in the ps_scan PROSITE scanning program, the standalone version of ScanProsite (6). ps_scan allows to scan a protein sequence (either from UniProtKB/Swiss-Prot or UniProtKB/TrEMBL or provided by the user) for the occurrence of patterns and profiles stored in the PROSITE database. The modified ps_scan program applies as default RDM1 and/or RDM2 when run with profiles for repetitive domains. Profiles for repetitive domains are tagged with 'R' and 'RR' or 'R?' in the TEXT field of the CUT_OFF lines (LEVEL=0 and LEVEL=-1) of the profile. When the profile is tagged with 'RR' the two methods RDM1 and RDM2 are applied, whereas when it is tagged with 'R?' only RDM1 is applied. In the output of the program the reported matches are tagged with 'R' or with 'r' when the hits have been detected with RDM1 or RDM2 respectively.

The PROSITE database is composed of two ASCII (text) files. The first
file (PROSITE.DAT) is a computer readable file that contains all the information
necessary to programs that will scan sequence(s) with patterns and/or matrices.
The second file (PROSITE.DOC) contains textual information that fully documents
each pattern and profile. We must point out that we strongly urge software
developers to build software tools that make use of both files. A list
of patterns or profiles present in a sequence is not very useful to biologists
without the relevant documentation.

III.B. Data file structure

III.B.1. Structure of an entry

The entries in the database data file (PROSITE.DAT) are structured
so as to be usable by human readers as well as by computer programs. Each
entry in the database is composed of lines. Different types of lines, each
with its own format, are used to record the various types of data which
make up the entry. The general structure of a line is the following:

Characters Content
---------- ----------------------------------------------------------
1 to 2 Two-character line code. Indicates the type of information
contained in the line.
3 to 5 Blank
6 up to 128 Data

The currently used line types, along with their respective line codes, are
listed below:

This section describes in detail the format of each type of line used in
the database data file (PROSITE.DAT).

III.C.1. The ID line

The ID (IDentification) line is always the first line of an entry.
The general form of the ID line is:

ID ENTRY_NAME; ENTRY_TYPE.

The first item on the ID line is the entry name. This name is a useful
means of identifying an entry. The entry name consists of from 2 to 21
uppercase alphanumeric characters. The characters that are allowed in an
entry name are: A-Z, 0-9, and the underscore character "_".

The second item on the ID line indicates the type of PROSITE entry.
Currently this can be one the following:

PATTERN
MATRIX

Examples:

ID ADH_ZINC; PATTERN.
ID SH3; MATRIX.

III.C.2. The AC line

The AC (ACcession number) line lists the accession number associated
with an entry. It is always the second line of an entry. Accession numbers
provide a stable way of identifying entries from release to release. It
is sometimes necessary for reasons of consistency to change the names of
the entries between releases.

An accession number, however, never change. Accession numbers allow
unambiguous citation of database entries. Researchers who wish to cite
a PROSITE entry in their publications should always cite the accession
number of that entry in order to ensure that readers can find the relevant
data in a subsequent release.
The format of the AC line is:

AC PSnnnnn;

Where 'PS' stands for PROSITE and 'nnnnn' is a five digit number. Example:

AC PS00123;

III.C.3. The DT line

The DT (DaTe) line shows the date of entry or last modification of
the entry. It is always the third line of an entry. The format of the DT
line is:

The first date indicates when the entry first appeared in the database.

The second date indicates when the 'primary' data of the entry was last modified. By this we mean the data relevant to the pattern or matrix being described in that entry (PA and MA lines)
as well as post-processing (PP) lines.

The third date indicates when any data other then the 'primary' data has been modified.

The PA (PAttern) lines contains the definition of a PROSITE pattern.
The patterns are described using the following conventions:

The standard IUPAC one-letter codes for the amino acids are used.

The symbol 'x' is used for a position where any amino acid is accepted.

Ambiguities are indicated by listing the acceptable amino acids for
a given position, between square parentheses '[ ]'. For example: [ALT]
stands for Ala or Leu or Thr.

Ambiguities are also indicated by listing between a pair of curly
brackets '{ }' the amino acids that are not accepted at a given position.
For example: {AM} stands for any amino acid except Ala and Met.

Each element in a pattern is separated from its neighbor by a '-'.

Repetition of an element of the pattern can be indicated by following
that element with a numerical value or a numerical range between parenthesis.
Examples: x(3) corresponds to x-x-x, x(2,4) corresponds to x-x or x-x-x
or x-x-x-x.

When a pattern is restricted to either the N- or C-terminal of a
sequence, that pattern either starts with a '<' symbol or respectively
ends with a '>' symbol.
In some rare cases (e.g. PS00267 or PS00539), '>' can also occur inside square
brackets for the C-terminal element. 'F-[GSTV]-P-R-L-[G>]' means that either
'F-[GSTV]-P-R-L-G' or 'F-[GSTV]-P-R-L>' are considered.

A period ends the pattern.

Examples:

PA [AC]-x-V-x(4)-{ED}.

This pattern is translated as: [Ala or Cys]-any-Val-any-any-any-any-{any
but Glu or Asp}

PA <A-x-[ST](2)-x(0,1)-V.

This pattern, which must be in the N-terminal of the sequence ('

III.C.6. The MA line

The MA (MAtrix) lines contain the definition of a PROSITE profile (or
matrix) entry. The exact format content of this line is fully described
in a specific document (profile.txt)
which is part of the PROSITE distribution files.

III.C.7. The PP line

PROSITE profiles normally use two cut-off levels, a reliable cut-off (LEVEL=0) and a low
confidence cut-off (LEVEL=-1). The low level cut-off usually covers the twilight
zone where few true positives, that cannot be separated from false positives, might be
present. The output of the pfsearch and the pfscan programs indicate strong
matches (level 0) with '!' and weak matches (level -1) with '?'. This specific tagging
in the match list can be used in post-processing, to validate some true positives
present in the twilight zone or to eliminate some false positives detected with significant
score.

We have already started to introduce some contextual information for the detection of repeat units,
where a weak match can be promoted in some particular cases (see Methodology to identify repeats) and we have now
generalized this approach to other contexts. To do so, we have introduced a new line type, PP
(for Post Processing), that defines the conditions to retrieve matches in post processing.

Four different types of post processing are defined as bellow:

PP /COMPETES_HIT_WITH: PS50001; PS50002(2); ...;

Overlapping matches between a profile and the one(s) listed in its PP line are in competition.
For each region of the protein matched by competing profiles only the match with the highest normalized score is kept.
The minimal size of the region of overlap to consider the match as overlapping can be specified between parentheses.
If no size is specified, no overlap is tolerated.

PP /COMPETES_SEQ_WITH: PS50001; PS50002; ...;

For each sequence matched by the two profiles only the one that produces the highest normalized
score is kept to annotate the protein.

PP /PROMOTED_BY: PS50001; PS50002; ...;

Weak matches (?) with the profile containing the PP line are promoted by the presence in the
protein of a strong match (!) with the profile(s) defined in the PP line.

PP /DEMOTED_BY: PS50001; PS50002; ...;

Strong matches (!) with the profile containing the PP line are demoted by the presence in the
protein of a match with the profile(s) defined in the PP line.

The PP line is located just after the last MA line as shown in the following example:

The NR (Numerical Results) lines contain information relevant to the
results of the scan with a pattern on the whole Swiss-Prot part of UniProtKB.
The format of the NR line is:

NR /QUALIFIER=data; /QUALIFIER=data; .......

The qualifiers that are currently defined are:

/RELEASE

UniProtKB release number and total number of sequence entries in the Swiss-Prot part of that release.

/TOTAL

Total number of hits in UniProtKB/Swiss-Prot.

/POSITIVE

Number of hits on proteins that are known to belong to the
set in consideration.

/UNKNOWN

Number of hits on proteins that could possibly belong to
the set in consideration.

/FALSE_POS

Number of false hits (on unrelated proteins).

/FALSE_NEG

Number of known missed hits.

/PARTIAL

Number of partial sequences which belong to the set in
consideration, but which are not hit by the pattern or
profile because they are partial (fragment) sequences.

The syntax of the /RELEASE qualifier is:

/RELEASE=nn,seq_num;

where 'nn' is a UniProtKB release number and 'seq_num' the total number
of UniProtKB/Swiss-Prot entries in that release.

For all other qualifiers the syntax is:

/QUALIFIER=x(y);

or

/QUALIFIER=y;

where 'x' represents the number of hits and 'y' the number of sequences.
In the majority of pattern entries 'x' will be equal to 'y', but for those
patterns that are designed to detect domains that can be repeated more
than once in a given sequence (for example: zinc-fingers, EF-hand regions,
kringle domain, etc.), 'x' can be larger than 'y'. Such a situation is
described in the following example:

In the above example the scan for the pattern (or profile) was done
on release 40.7 of UniProtKB/Swiss-Prot which contained 103373 sequence entries, that
pattern (or profile) was found 123 times in 56 different sequences (/TOTAL).
Out of those 123 'hits', 115 were produced by 51 sequences that belong
to the set under consideration (/POSITIVE), 5 hits were produced by two
sequences which could possible belong to the set (/UNKNOWN) and 3 hits
were produced by 3 other sequences (/FALSE_POS). That particular pattern
missed 3 sequences (/FALSE_NEG) and there were two partial sequences that
belong to the set under consideration but which do not include the region
that contains that pattern (or profile) (/PARTIAL).

Note: for some degenerate patterns (as for example the N-glycosylation
consensus pattern), the NR lines are not provided as they would not yield
any useful information.

III.C.9. The CC line

The CC (Comments) lines contains various types of comments. The format
of the CC line is:

CC /QUALIFIER=data; /QUALIFIER=data; .......

The qualifiers that are currently defined are:

/TAXO_RANGE

Taxonomic range.

/MAX-REPEAT

Maximum known number of repetitions of the pattern or profile in a
single protein.

/SITE

Indication of an `interesting' site in a pattern.

/SKIP-FLAG

Indication of an entry that can be, in some cases,
ignored by a program (because it is too unspecific).

/VERSION

The version number of a pattern or a profile.

There are 5 qualifiers specific to profile entries:

/MATRIX_TYPE

Describes the region of the protein identified by the profile.

/SCALING_DB

Scaling database used to calibrate the profile.

/AUTHOR

Author of the profile.

/FT_KEY

Feature key to describe the region covered by the profile.

/FT_DESC

Feature description of the region covered by the profile.

III.C.9.i. The /TAXO-RANGE qualifier

This qualifier is used to indicate the taxonomic range of a pattern
or matrix. The syntax of that qualifier is the following:

/TAXO-RANGE=ABEPV;

where:

'A' stands for archaea

'B' stands for bacteriophages

'E' stands for eukaryotes

'P' stands for prokaryotes (bacteria)

'V' stands for eukaryotic viruses

When the pattern or matrix entry has no relevance to one of the above
taxonomic classes a question mark ('?') replaces the corresponding letter
symbol. Example:

/TAXO-RANGE=A?E??

would be used in an entry relevant to proteins
of archeal ('A') and eukaryotic ('E') origin.

Note: the /TAXO-RANGE qualifier does not take into account false positive
hits. For example: if a pattern produces one or more false positive hit(s)
on bacteriophage protein(s) but no true positive results were obtained
on any bacteriophage proteins, a question mark will be present instead
of the 'B' in the second position of the /TAXO-RANGE qualifier.

III.C.9.ii. The /MAX-REPEAT qualifier

This qualifier is used to indicate the maximum number of times a given
pattern or profile has been found in a single protein sequence. The syntax
of that qualifier is the following:

/MAX-REPEAT=nn;

For example, in the CC lines of the pattern entry to detect an EF-hand
calcium-binding domain we have:

/MAX-REPEAT=8

This indicates that up to 8 copies of the EF-hand domain are known to be present in at least one
protein sequence.

Notes: One should not make the assumption that the value indicated by this
qualifier is equivalent to the maximum number of hits that will be obtained
by the pattern or profile being described; it is not uncommon that a pattern
or a profile will not detect all occurrences of a repeated domain.

III.C.9.iii.The /SITE qualifier

This qualifier is used to indicate the position of an 'interesting'
site in a pattern or a profile. For example, if a pattern includes an active
site residue, the /SITE qualifier will be used to indicate the position
of that residue in the pattern. The syntax of this qualifier is the following:

/SITE=nn,text_description;

where 'nn' is the position in the pattern or the profile of the site
being described and 'text_description' a textual description of that site. Examples:

/SITE=3,active_site;
/SITE=5,disulfide;

Notes:

For pattern entries, the position numbering is indicated in pattern
element units. For example if we want to indicate that the 'C' in the pattern
'<A-[ILMV]-x(2,4)-A-C-P' is involved in a disulfide bond we would indicate
'/SITE=5,disulfide;', the 'C' being the fifth element in the pattern.

For profile (matrix) entries, the position numbering relates to match
positions.

If necessary there can be more than one /SITE qualifier in the CC line(s)
of an entry. For example in the pattern entry specific to proteins of the
cytochrome c family, the pattern 'C-{CPWHF}-{CPWR}-C-H-{CFWY}' has the
following /SITE qualifiers in its CC lines:

/SITE=1,heme; /SITE=4,heme; /SITE=5,heme_iron;

This to indicate that the two 'C's are the residues that bind the heme
group and that the 'H' is an axial ligand to the heme iron.

If the presence of a site is assumed, but experimental data is lacking,
a '(?)' is appended at the end of the text description. For example if
we have the pattern 'A-x(2)-C-R' and the cysteine in that pattern is thought
to be involved in a disulfide bond, it would be indicated as:

/SITE=3,disulfide(?);

III.C.9.iv. The /SKIP-FLAG qualifier

Some PROSITE entries such as those describing commonly found post-translational
modifications (a typical example is N-glycosylation) are found in the majority
of known protein sequences. While it is generally useful to note their
presence, some programs may want, in some cases, to ignore those entries.
For this purpose these entries are indicated with the following qualifier
in their CC lines:

/SKIP-FLAG=TRUE;

III.C.9.v. The /VERSION qualifier

The version number (an integer) is incremented only when a modification takes place in PA or
MA lines. Version numbers have been introduced in release 19.0 and were all set to version one.
Example:

/VERSION=1;

III.C.9.vi. The /MATRIX_TYPE qualifier

This qualifier describes the region in the protein identified by the profile.
Example:

/MATRIX_TYPE=protein_domain;

The matrix type can be protein_domain, repeat_region, localization_signal or
composition where:

Protein_domain

Describes a profile directed against a conserved region of a protein.

Repeat_region

Describes a profile directed against a run of repeat units.

Localization_signal

Describes a profile directed against a region important for the
localization of protein in the cell.

Composition

Describes a profile directed against a region of low complexity or
enriched in a given amino acid.

III.C.9.vii. The /SCALING_DB qualifier

This qualifier indicates which database was used to calibrate the profile.
Example:

/SCALING_DB=window20_shuffled;

Scaling databases currently used are:

reversed

Is a protein database, randomized by taking the reverse sequence of
each individual entry.

window20

Is a protein database, locally shuffled in windows of 20 residues.

window20_shuffled

Is a small version of a window20 protein database.

db_global

Is a protein database, globally shuffled in windows of 20 residues.

III.C.9.viii. The /AUTHOR qualifier

This qualifier is used to indicate the author that created or updated the
profile. Example:

/AUTHOR=K_Hofmann, P_Bucher;

The first name is the author of the profile, the second one the author of the last update.

III.C.9.ix. The /FT_KEY and /FT_DESC qualifiers

These qualifiers are used to give a computer readable short description of
the region identified by the profile. They are based on the UniProtKB
Feature Table key and Feature Table description currently used to define the
region identified by the profile. Example:

/FT_KEY=DOMAIN; /FT_DESC=KRINGLE.

FT_KEY can be NP_BIND, MOTIF, DOMAIN, REPEAT, DNA_BIND or ZN_FING. More details
can be found on feature keys and feature descriptions in the
UniProtKB user manual.

III.C.10. The DR line

The DR (Database Reference) lines are used as pointers to the UniProtKB/Swiss-Prot
entries that are picked up (or missed) by the pattern being described in
the entry. The format of the DR line is:

DR AC_NB, ENTRY_NAME, C; AC_NB, ENTRY_NAME, C; AC_NB, ENTRY_NAME, C;

where:

'AC_NB' is the UniProtKB/Swiss-Prot primary accession number of the entry to
which reference is being made.

'ENTRY_NAME' is the UniProtKB/Swiss-Prot entry name.

'C' is a one character flag that can be one of the following:

T

For a true positive.

P

For a 'potential' hit; a sequence that belongs to the set under
consideration, but which was not picked up because the region(s)
that are used as a 'fingerprint' (pattern or profile) is not yet
available in the database (partial sequence).

N

For a false negative; a sequence which belongs to the set under
consideration, but which has not been picked up by the pattern or
profile.

?

For an unknown; a sequence which possibly could belong to the set
under consideration.

F

For a false positive; a sequence which does not belong to the set in
consideration.

In the above example, we have pointers to 17 UniProtKB/Swiss-Prot sequences which
are true positives ('T'), eight which are potential hits ('P'), six which
have been missed ('N'), three sequences that may belong to the set under
consideration ('?'), and six sequences that are false positives ('F').

III.C.11. The 3D line

The 3D (3D-structure) line is used to list the code(s) of the
Protein Data Bank (PDB) entries that contain structural data corresponding
the sequence region described in a PROSITE entry. The format of the 3D
line is:

3D name; [name2;...]

Example:

3D 7WGA; 9WGA; 1WGC; 2WGC;

III.C.12. The PR line

PROSITE is now complemented with a set of rules,
ProRule, which are used to give
extra meaningful information when a match with a PROSITE profile or pattern
is detected. Each rule is triggered by a PROSITE entry and contains
information linked to the domain or protein family covered by the
profile/pattern. This information can be general, e.g. always
associated with the domain or protein family, or conditional, depending on
the presence of particular residues in functionally or structurally critical
positions. The rule(s) associated with a profile/pattern is cross-referenced
in the profile/pattern entry in a new line type (PR line).

Example:

PR PRU00001;

The PR line is located just before the DO line as shown in the following
example:

The first line '{PDOCnnnnn}', where 'nnnnn' is a five digit number
is the documentation entry accession number.

The following lines '{PSmmmmm; ENTRY_NAME}' list the accession number
and entry name of the PROSITE data file entri(es) that correspond to the
documentation entry.

The documentation text lines are in ordinary English and are
free-format. The only restriction is that they do not start with the
character '{'.

Reference to other PROSITE documentation is indicated as followed:
(see <PDOC00100>)

Reference to PDB entries are indicated as followed:

(see <PDB:1A4B>)
or
(see <PDB:1J5E; M>) where M is the name of a chain.

As an example, we show here a section of the documentation file that
contains two entries.

{PDOC00082}
{PS00087; SOD_CU_ZN_1}
{PS00332; SOD_CU_ZN_2}
{BEGIN}
***********************************************
* Copper/Zinc superoxide dismutase signatures *
***********************************************
Copper/Zinc superoxide dismutase (EC 1.15.1.1) (SODC) [1] is one of the three
forms of an enzyme that catalyzes the dismutation of superoxide radicals. SODC
binds one atom each of zinc and copper. Various forms of SODC are known: a
cytoplasmic form in eukaryotes, an additional chloroplast form in plants, an
extracellular form in some eukaryotes, and a periplasmic form in prokaryotes.
The metal binding sites are conserved in all the known SODC sequences [2].
We derived two signature patterns for this family of enzymes: the first one
contains two histidine residues that bind the copper atom; the second one is
located in the C-terminal section of SODC and contains a cysteine which is
involved in a disulfide bond.
-Consensus pattern: [GA]-[IMFAT]-H-[LIVF]-H-x(2)-[GP]-[SDG]-x-[STAGDE]
[The two H's are copper ligands]
-Sequences known to belong to this class detected by the pattern: ALL.
-Other sequence(s) detected in UniProtKB/Swiss-Prot: 5.
-Consensus pattern: G-[GN]-[SGA]-G-x-R-x-[SGA]-C-x(2)-[IV]
[C is involved in a disulfide bond]
-Sequences known to belong to this class detected by the pattern: ALL.
-Other sequence(s) detected in UniProtKB/Swiss-Prot: NONE.
-Note: these patterns will not detect proteins related to SODC, but which have
lost their catalytic activity, such as Vaccinia virus protein A45.
-Last update: July 1999 / Patterns and text revised.
[ 1] Bannister J.V., Bannister W.H., Rotilio G.
CRC Crit. Rev. Biochem. 22:111-154(1987).
[ 2] Smith M.W., Doolittle R.F.
J. Mol. Evol. 34:175-184(1992).
{END}
{PDOC00083}
{PS00088; SOD_MN}
{BEGIN}
******************************************************
* Manganese and iron superoxide dismutases signature *
******************************************************
Manganese superoxide dismutase (EC 1.15.1.1) (SODM) [1] is one of the three
forms of an enzyme that catalyzes the dismutation of superoxide radicals. The
four ligands of the manganese atom are conserved in all the known SODM
sequences. These metal ligands are also conserved in the related iron form of
superoxide dismutases [2,3]. We selected, as a signature, a short conserved
region which includes two of the four ligands: an aspartate and a histidine.
-Consensus pattern: D-x-W-E-H-[STA]-[FY](2)
[D and H are manganese/iron ligands]
-Sequences known to belong to this class detected by the pattern: ALL.
-Other sequence(s) detected in UniProtKB/Swiss-Prot: NONE.
-Last update: June 1992 / Text revised.
[ 1] Bannister J.V., Bannister W.H., Rotilio G.
CRC Crit. Rev. Biochem. 22:111-154(1987).
[ 2] Parker M.W., Blake C.C.F.
FEBS Lett. 229:377-382(1988).
[ 3] Smith M.W., Doolittle R.F.
J. Mol. Evol. 34:175-184(1992).
{END}